Multiple Experts Knowledge in Fuzzy Optimization of Logistic Networks

  • Juan Carlos Figueroa-García
  • Dusko Kalenatic
  • Cesar Amilcar López-Bello
Chapter
First Online:
Part of the Intelligent Systems Reference Library book series (ISRL, volume 87)

Abstract

Uncertainty in logistic networks is commonly handled by probabilistic tools, but sometimes the required statistical information is not available, so the experts of the network take an important role in decision making without statistical information. Some soft computing techniques such as fuzzy sets are useful to represent the knowledge of the experts because they can be combined with optimization models to find a set of possible choices to be taken in different scenarios. In this chapter, we present an application of fuzzy optimization models and methods to a logistic network design problem using linguistic information coming from multiple experts.

Keywords

Membership Function Logistic Network Fuzzy Optimization Soft Computing Technique Linguistic Label 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Juan Carlos Figueroa-García
    • 1
  • Dusko Kalenatic
    • 2
  • Cesar Amilcar López-Bello
    • 1
  1. 1.Engineering DepartmentUniversidad Distrital Francisco José de CaldasBogotáColombia
  2. 2.Universidad de La SabanaChíaColombia

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